Cancer risk gene screening method, device, equipment and storage medium

Abstract

The present application relates to the field of bioinformatics, and provides a screening method, device, equipment and storage medium for cancer risk genes. The method includes: obtaining the cfDNA sequencing data of the subject, detecting the cfDNA sequencing data based on a preset variant gene detection algorithm, and obtaining the variant gene information of the subject; wherein the variant gene information includes at least one variant gene; for each variant gene, generating the risk score information corresponding to the variant gene based on a preset risk scoring algorithm; wherein the risk score information includes multiple mapping relationships, and the mapping relationship is a mapping relationship between cancer type and risk score; constructing a variant gene-cancer type topology map based on each of the risk score information; the variant gene-cancer type topology map is the cancer risk gene screening result. This method helps to provide clinicians with a more accurate cancer risk analysis, thereby improving the accuracy of diagnosis.

Description

Technical Field

[0001] The present application relates to the field of bioinformatics, and in particular to a method, device, equipment and storage medium for screening cancer risk genes. Background Art

[0002] Cancer is one of the leading causes of death worldwide, and early screening and diagnosis are crucial to improving patient survival rates. In the development of cancer, genetic mutations are likely to occur, especially mutations in specific oncogenes and tumor suppressor genes, which are closely related to the formation and progression of cancer. Therefore, mutant gene detection technology is widely used in early screening of cancer. However, existing mutant gene detection methods usually focus on identifying the presence of mutant genes and lack a comprehensive analysis of the carcinogenic risk of mutant genes. At the same time, existing methods make it difficult to intuitively show the correlation between mutant genes and cancer types. Summary of the invention

[0003] The present application provides a method, device, equipment and storage medium for screening cancer risk genes to solve the problems raised by the above-mentioned background technology.

[0004] In a first aspect, the present application provides a method for screening cancer risk genes, comprising:

[0005] Acquire cfDNA sequencing data of the subject, and detect the cfDNA sequencing data based on a preset variant gene detection algorithm to obtain variant gene information of the subject; wherein the variant gene information includes at least one variant gene;

[0006] For each of the variant genes, risk score information corresponding to the variant gene is generated based on a preset risk score algorithm; wherein the risk score information includes a plurality of mapping relationships, and the mapping relationship is a mapping relationship between a cancer type and a risk score;

[0007] A variant gene-cancer type topology map is constructed based on each of the risk score information; the variant gene-cancer type topology map is the cancer risk gene screening result.

[0008] In a possible implementation, generating risk score information corresponding to the variant gene based on a preset risk score algorithm includes:

[0009] Obtaining the correlation coefficients between the variant genes and each cancer type based on a preset Bayesian formula;

[0010] Obtaining a global risk coefficient corresponding to the variant gene information based on a preset global risk coefficient calculation formula;

[0011] For each of the cancer types, a risk score corresponding to the cancer type is generated based on a preset risk score calculation formula, the global risk coefficient and a correlation coefficient corresponding to the cancer type to obtain the risk score information.

[0012] In a possible implementation, the Bayesian formula is as shown in formula (1):

[0013] ,

[0014] in, P(V cancer ) is the correlation coefficient; P ( V detected∣cancer ) is the conditional probability; P(cancer) is the basic probability; e −λf(ΔG) is an exponential decay term, which is used to reflect the effect of gene mutation on the change of protein free energy. λ is the regulating factor; f(ΔG) is the free energy change function; ΔG is the free energy change of protein before and after gene mutation; P(V detected) is the overall probability; N(V) is the background mutation rate; for each of the cancer types, when calculating the correlation coefficient between the cancer type and the variant gene, the conditional probability is the probability of detecting the variant gene in the patient corresponding to the cancer type, the basic probability is the probability of the cancer type appearing in the population, the overall probability is the probability of the variant gene appearing in the population, and the background mutation rate is the probability of the variant gene appearing in the non-cancer population.

[0015] In a possible implementation, the global risk coefficient calculation formula is shown in formula (2):

[0016] ,

[0017] in, I(V) is the global risk coefficient, B i For the i The centrality score corresponding to each variant gene in the gene regulatory network, W is the interaction strength between each variant gene, N i For the i The number of interactions corresponding to each variant gene in the gene regulatory network.

[0018] In a possible implementation, the risk score calculation formula is shown in formula (3):

[0019] ,

[0020] in, S(V) scoring the risk, I(V) is the global risk coefficient, P(V cancer ) is the correlation coefficient, N is the number of interactions corresponding to the variant gene in the gene regulatory network, B is the centrality score of the variant gene in the gene regulatory network.

[0021] In a possible implementation, constructing a variant gene-cancer type topology map based on each of the risk score information includes:

[0022] Arrange the variant genes corresponding to the risk score information in order from top to bottom to obtain a variant gene sequence;

[0023] Deduplication processing is performed on all cancer types in each of the risk score information to obtain target cancer type information; the target cancer type information includes multiple target cancer types;

[0024] Arrange the target cancer types in order from top to bottom to obtain a target cancer type sequence;

[0025] Placing the target cancer type sequence to the right of the variant gene sequence;

[0026] For each of the risk score information, the variant genes corresponding to the risk score information in the variant gene sequence and the target cancer types corresponding to each mapping relationship of the risk score information in the target cancer type sequence are respectively connected with straight lines, and the risk score corresponding to the target cancer type corresponding to the straight line in the risk score information is marked on each of the straight lines with a first font, to obtain an initial variant gene-cancer type topology map;

[0027] For each variant gene on the initial variant gene-cancer type topology map, the risk scores corresponding to each straight line corresponding to the variant gene on the initial variant gene-cancer type topology map are added to obtain a gene risk score corresponding to the variant gene, and the gene risk score is marked next to the variant gene in a second font to obtain an intermediate variant gene-cancer type topology map;

[0028] For each cancer type on the intermediate variant gene-cancer type topology map, the risk scores corresponding to each straight line corresponding to the cancer type on the initial variant gene-cancer type topology map are added to obtain the cancer risk score corresponding to the cancer type, and the cancer risk score is marked next to the cancer type in a third font to obtain the variant gene-cancer type topology map.

[0029] In a possible implementation, the method further includes:

[0030] Obtaining a test code of the test subject; the test code includes a plurality of numbers and a plurality of letters;

[0031] Encoding the mutant gene-cancer type topological map based on a preset encoding rule to obtain a coding sequence;

[0032] The coding sequence is segmented based on the number of letters to obtain a plurality of coding units, and the coding units are arranged in sequence based on the corresponding order of the coding units in the coding sequence to obtain a coding unit sequence; wherein the number of the coding units is consistent with the number of letters;

[0033] Performing hash operations on each of the letters based on a preset hash algorithm to obtain a hash value corresponding to each letter, and arranging each of the hash values ​​in sequence based on the order of the letters corresponding to each of the hash values ​​in the checked code to obtain a hash value sequence;

[0034] For each coding unit in the coding unit sequence, a target hash value corresponding to the coding unit is determined in the hash value sequence, and the coding unit is encrypted based on the target hash value to obtain an encrypted coding unit corresponding to the coding unit, and the encrypted coding unit is packaged based on a preset package processing method to obtain a target data packet corresponding to the encrypted coding unit; wherein the order of the coding units in the coding unit sequence is consistent with the order of the target hash values ​​in the hash value sequence;

[0035] For each of the numbers, a data packet unit corresponding to the number is generated based on a preset data packet unit generation method, and the number of data packets in the data packet unit is consistent with the number;

[0036] Arrange the data packet units in sequence based on the order of the numbers corresponding to the data packet units in the checked code to obtain a data packet unit sequence;

[0037] For each of the letters, based on the order of the letters in the checked code and the order of the numbers corresponding to each of the data packet units in the checked code, determine the interpolation position corresponding to the letter in the data packet unit sequence;

[0038] For each of the target data packets, insert the target data packet into the interpolation position corresponding to the letter corresponding to the target data packet to obtain a target data packet sequence;

[0039] Each data packet of the target data packet sequence is sent to the subject in sequence.

[0040] In a second aspect, the present application provides a screening device for cancer risk genes, comprising:

[0041] An acquisition module, used to acquire cfDNA sequencing data of the subject, and detect the cfDNA sequencing data based on a preset variant gene detection algorithm to obtain variant gene information of the subject; wherein the variant gene information includes at least one variant gene;

[0042] A scoring module, for generating risk score information corresponding to each of the variant genes based on a preset risk scoring algorithm; wherein the risk score information includes a plurality of mapping relationships, and the mapping relationship is a mapping relationship between a cancer type and a risk score;

[0043] A construction module is used to construct a variant gene-cancer type topology map based on each of the risk score information; the variant gene-cancer type topology map is the cancer risk gene screening result.

[0044] In a third aspect, the present application provides a terminal device, comprising a processor, a memory, and a computer program stored in the memory and executable by the processor, wherein when the computer program is executed by the processor, the cancer risk gene screening method as described above is implemented.

[0045] In a fourth aspect, the present application provides a computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, wherein when the computer program is executed by a processor, the screening method for cancer risk genes as described above is implemented.

[0046] The present application provides a screening method, apparatus, device and storage medium for cancer risk genes, wherein the method comprises: obtaining cfDNA sequencing data of a subject, detecting the cfDNA sequencing data based on a preset variant gene detection algorithm, and obtaining variant gene information of the subject; wherein the variant gene information comprises at least one variant gene; for each variant gene, generating risk score information corresponding to the variant gene based on a preset risk scoring algorithm; wherein the risk score information comprises a plurality of mapping relationships, wherein the mapping relationship is a mapping relationship between a cancer type and a risk score; constructing a variant gene-cancer type topological map based on each risk score information; the variant gene-cancer type topological map is a cancer risk gene screening result. This method, on the one hand, obtains the correlation coefficients between the variant genes and each cancer type based on a preset Bayesian formula; and obtains the global risk coefficient corresponding to the variant gene information based on a preset global risk coefficient calculation formula; and for each cancer type, generates a risk score corresponding to the cancer type based on a preset risk score calculation formula, the global risk coefficient and the correlation coefficient corresponding to the cancer type, to obtain the risk score information. This multi-dimensional evaluation method helps to provide clinicians with more accurate cancer risk analysis, thereby improving the accuracy of diagnosis. On the other hand, by generating a variant gene-cancer type topology map, it can intuitively display the risk associations between different variant genes and multiple cancer types, so that doctors can intuitively understand the pathogenic risk of each variant gene in different cancers. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0048] Figure 1 A schematic diagram of a method for screening cancer risk genes provided in an embodiment of the present application;

[0049] Figure 2 A schematic block diagram of the structure of a cancer risk gene screening device provided in an embodiment of the present application;

[0050] Figure 3 A schematic block diagram of the structure of a terminal device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0051] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0052] The flowcharts shown in the accompanying drawings are only examples and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may also be decomposed, combined or partially merged, so the actual execution order may change based on actual conditions.

[0053] It should also be understood that the terms used in this application specification are only for the purpose of describing specific embodiments and are not intended to limit the application. As used in this application specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0054] It should be further understood that the term “and / or” used in the specification and appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0055] Cancer is one of the leading causes of death worldwide, and early screening and diagnosis are crucial to improving patient survival rates. In the development of cancer, genetic mutations are easily caused, especially mutations in specific oncogenes and tumor suppressor genes, which are closely related to the formation and progression of cancer. Therefore, the detection technology of mutant genes is widely used in early screening of cancer. However, existing mutant gene detection methods usually focus on identifying the existence of mutant genes, and lack a comprehensive analysis of the carcinogenic risk of mutant genes. At the same time, existing methods are difficult to intuitively show the correlation between mutant genes and cancer types. To this end, the present application provides a screening method, device, equipment and storage medium for cancer risk genes to solve the above problems.

[0056] In conjunction with the accompanying drawings, some embodiments of the present application are described in detail below. In the absence of conflict, the following embodiments and features in the embodiments can be combined with each other.

[0057] See also Figure 1 , Figure 1 A schematic diagram of the process of screening cancer risk genes provided in the embodiments of the present application is shown in FIG. Figure 1 As shown, the method for screening cancer risk genes provided in the embodiment of the present application includes steps S1 to S3.

[0058] Step S1, obtaining the cfDNA sequencing data of the subject, and detecting the cfDNA sequencing data based on a preset variant gene detection algorithm to obtain the variant gene information of the subject; wherein the variant gene information includes at least one variant gene.

[0059] Specifically, first, a cfDNA sample is extracted from the subject's blood sample, and then the cfDNA sample is sequenced using a high-throughput sequencing platform (such as Illumina, BGI, etc.) to obtain the cfDNA sequencing data. Finally, the cfDNA sequencing data is detected based on a preset variant gene detection algorithm to obtain the subject's variant gene information, usually by comparing the cfDNA sequencing data with a genome reference sequence (such as GRCh38) to obtain the variant gene information.

[0060] Step S2: for each of the variant genes, generate risk score information corresponding to the variant gene based on a preset risk score algorithm; wherein the risk score information includes multiple mapping relationships, and the mapping relationship is a mapping relationship between cancer type and risk score.

[0061] Specifically, the risk score information corresponding to the variant gene is generated based on a preset risk score algorithm, including: obtaining the correlation coefficients between the variant gene and each cancer type based on a preset Bayesian formula; obtaining the global risk coefficient corresponding to the variant gene information based on a preset global risk coefficient calculation formula; for each cancer type, generating the risk score corresponding to the cancer type based on the preset risk score calculation formula, the global risk coefficient and the correlation coefficient corresponding to the cancer type, to obtain the risk score information.

[0062] The Bayesian formula is shown in formula (1):

[0063] ,

[0064] in, P(V cancer ) is the correlation coefficient; P ( V detected∣cancer ) is the conditional probability; P(cancer) is the basic probability; e −λf(ΔG) is an exponential decay term, which is used to reflect the effect of gene mutation on the change of protein free energy. λ is the regulating factor; f(ΔG) is the free energy change function; ΔG is the free energy change of protein before and after gene mutation; P(V detected) is the overall probability; N(V) is the background mutation rate; for each of the cancer types, when calculating the correlation coefficient between the cancer type and the variant gene, the conditional probability is the probability of detecting the variant gene in the patient corresponding to the cancer type, the basic probability is the probability of the cancer type appearing in the population, the overall probability is the probability of the variant gene appearing in the population, and the background mutation rate is the probability of the variant gene appearing in the non-cancer population; wherein, P ( V detected∣cancer ), P(cancer), λ, f(ΔG), ΔG, P(V detected)、 N(V) All can be obtained through medical databases or medical literature libraries.

[0065] The global risk coefficient calculation formula is shown in formula (2):

[0066] ,

[0067] in, I(V) is the global risk coefficient, B i For the i The centrality score corresponding to each variant gene in the gene regulatory network, W is the interaction strength between each variant gene, N i For the i The number of interactions corresponding to each variant gene in the gene regulatory network; by inputting the variant gene and the gene regulatory network into computational tools such as Cytoscape and Gephi, we can obtain B i For each variant gene in the variant gene information, the binding force scores between the variant gene and the remaining variant genes in the variant gene information are obtained through the STRIN database, and the obtained binding force scores are added together to obtain the interaction strength. Ni Specifically, i The number of genes directly connected to the variant gene in the gene regulatory network.

[0068] The risk score calculation formula is shown in formula (3):

[0069] ,

[0070] in, S(V) scoring the risk, I(V) is the global risk coefficient, P(Vcancer) is the correlation coefficient, N is the number of interactions corresponding to the variant gene in the gene regulatory network, Bis the centrality score of the variant gene in the gene regulatory network.

[0071] Step S3, constructing a variant gene-cancer type topology map based on each of the risk score information; the variant gene-cancer type topology map is a cancer risk gene screening result.

[0072] Among them, the construction of the variant gene-cancer type topological map based on each of the risk score information includes: arranging the variant genes corresponding to each of the risk score information in order from top to bottom to obtain a variant gene sequence; deduplicating all cancer types in each of the risk score information to obtain target cancer type information; the target cancer type information includes multiple target cancer types; arranging each of the target cancer types in order from top to bottom to obtain a target cancer type sequence; placing the target cancer type sequence on the right side of the variant gene sequence; for each of the risk score information, connecting the variant genes corresponding to the risk score information in the variant gene sequence and each target cancer type corresponding to each mapping relationship of the risk score information in the target cancer type sequence with a straight line, and marking the target cancer type corresponding to the straight line with a first font on each of the straight lines. The risk score corresponding to the type in the risk score information is obtained to obtain an initial variant gene-cancer type topology map; for each variant gene on the initial variant gene-cancer type topology map, the risk scores corresponding to each straight line corresponding to the variant gene on the initial variant gene-cancer type topology map are added to obtain the gene risk score corresponding to the variant gene, and the gene risk score is marked next to the variant gene with a second font to obtain an intermediate variant gene-cancer type topology map; for each cancer type on the intermediate variant gene-cancer type topology map, the risk scores corresponding to each straight line corresponding to the cancer type on the initial variant gene-cancer type topology map are added to obtain the cancer risk score corresponding to the cancer type, and the cancer risk score is marked next to the cancer type with a third font to obtain the variant gene-cancer type topology map.

[0073] The method provided in this embodiment, on the one hand, obtains the correlation coefficient between the variant gene and each cancer type based on a preset Bayesian formula; and obtains the global risk coefficient corresponding to the variant gene information based on a preset global risk coefficient calculation formula; and for each cancer type, generates a risk score corresponding to the cancer type based on a preset risk score calculation formula, the global risk coefficient and the correlation coefficient corresponding to the cancer type, to obtain the risk score information. This multi-dimensional evaluation method helps to provide clinicians with more accurate cancer risk analysis, thereby improving the accuracy of diagnosis. On the other hand, by generating a variant gene-cancer type topology map, the risk association between different variant genes and multiple cancer types can be intuitively displayed, so that doctors can intuitively understand the pathogenic risk of each variant gene in different cancers.

[0074] In some embodiments, the method further comprises:

[0075] Obtaining a test code of the test subject; the test code includes a plurality of numbers and a plurality of letters;

[0076] Encoding the mutant gene-cancer type topological map based on a preset encoding rule to obtain a coding sequence;

[0077] The coding sequence is segmented based on the number of letters to obtain a plurality of coding units, and the coding units are arranged in sequence based on the corresponding order of the coding units in the coding sequence to obtain a coding unit sequence; wherein the number of the coding units is consistent with the number of letters;

[0078] Performing hash operations on each of the letters based on a preset hash algorithm to obtain a hash value corresponding to each letter, and arranging each of the hash values ​​in sequence based on the order of the letters corresponding to each of the hash values ​​in the checked code to obtain a hash value sequence;

[0079] For each coding unit in the coding unit sequence, a target hash value corresponding to the coding unit is determined in the hash value sequence, and the coding unit is encrypted based on the target hash value to obtain an encrypted coding unit corresponding to the coding unit, and the encrypted coding unit is packaged based on a preset package processing method to obtain a target data packet corresponding to the encrypted coding unit; wherein the order of the coding units in the coding unit sequence is consistent with the order of the target hash values ​​in the hash value sequence;

[0080] For each of the numbers, a data packet unit corresponding to the number is generated based on a preset data packet unit generation method, and the number of data packets in the data packet unit is consistent with the number;

[0081] Arrange the data packet units in sequence based on the order of the numbers corresponding to the data packet units in the checked code to obtain a data packet unit sequence;

[0082] For each of the letters, based on the order of the letters in the checked code and the order of the numbers corresponding to each of the data packet units in the checked code, determine the interpolation position corresponding to the letter in the data packet unit sequence; specifically, determine the serial number of the letters based on the order of the letters in the checked code, and determine the serial number of each of the numbers based on the order of the numbers in the checked code; map the serial number of each of the numbers to the data packet unit corresponding to the number to obtain the serial number of each of the data packet units; determine the interpolation position corresponding to the letter in the data packet unit sequence based on the serial number of the letter;

[0083] For each of the target data packets, insert the target data packet into the interpolation position corresponding to the letter corresponding to the target data packet to obtain a target data packet sequence;

[0084] Each data packet of the target data packet sequence is sent to the subject in sequence.

[0085] The method provided in this embodiment, on the one hand, improves the security of data during transmission by encoding the mutant gene-cancer type topology map of the subject, dividing the encoding sequence based on the number of letters to obtain multiple encoding units, and encrypting each encoding unit separately. On the other hand, for each target data packet, the target data packet is inserted into the interpolation site corresponding to the letter corresponding to the target data packet to obtain a target data packet sequence, thereby further improving the security of data during transmission. On the other hand, by sending each data packet of the target data packet sequence to the subject in sequence, it helps to improve the stability of the network transmission process and avoid transmission interruption or delay caused by excessive data.

[0086] See also Figure 2 , Figure 2 A schematic block diagram of the structure of a cancer risk gene screening device 100 provided in an embodiment of the present application is shown in FIG. Figure 2 As shown, the cancer risk gene screening device 100 comprises:

[0087] The acquisition module 110 is used to obtain the cfDNA sequencing data of the subject, detect the cfDNA sequencing data based on a preset variant gene detection algorithm, and obtain the variant gene information of the subject; wherein the variant gene information includes at least one variant gene.

[0088] The scoring module 120 is used to generate risk score information corresponding to each of the variant genes based on a preset risk scoring algorithm; wherein the risk score information includes multiple mapping relationships, and the mapping relationship is a mapping relationship between cancer type and risk score.

[0089] The construction module 130 is used to construct a variant gene-cancer type topology map based on each of the risk score information; the variant gene-cancer type topology map is a cancer risk gene screening result.

[0090] It should be noted that technicians in the relevant technical field can clearly understand that for the convenience and simplicity of description, the specific working process of the above-described device and each module can refer to the corresponding process in the aforementioned cancer risk gene screening method embodiment, and will not be repeated here.

[0091] The terminal device 200 provided in the above embodiment can be implemented in the form of a computer program. The computer program can be Figure 3 The system is run on the terminal device 200 shown.

[0092] See also Figure 3 , Figure 3 The present invention provides a schematic block diagram of the structure of a terminal device 200 according to an embodiment of the present application. The terminal device 200 includes a processor 201 and a memory 202. The processor 201 and the memory 202 are connected via a device bus 203, wherein the memory 202 may include a non-volatile storage medium and an internal memory.

[0093] The non-volatile storage medium can store a computer program. The computer program includes program instructions, and when the program instructions are executed by the processor 201, the processor 201 can execute any of the above-mentioned cancer risk gene screening methods.

[0094] The processor 201 is used to provide computing and control capabilities to support the operation of the entire terminal device 200.

[0095] The internal memory provides an environment for the operation of the computer program in the non-volatile storage medium. When the computer program is executed by the processor 201, the processor 201 can execute any of the above-mentioned cancer risk gene screening methods.

[0096] Those skilled in the art will understand that Figure 3 The structure shown in the figure is only a block diagram of a partial structure related to the scheme of the present application, and does not constitute a limitation on the terminal device 200 involved in the scheme of the present application. The specific terminal device 200 may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0097] It should be understood that the processor 201 may be a central processing unit (CPU), and the processor 201 may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0098] In some embodiments, the processor 201 is used to run a computer program stored in the memory to implement the following steps:

[0099] Acquire cfDNA sequencing data of the subject, and detect the cfDNA sequencing data based on a preset variant gene detection algorithm to obtain variant gene information of the subject; wherein the variant gene information includes at least one variant gene;

[0100] For each of the variant genes, risk score information corresponding to the variant gene is generated based on a preset risk score algorithm; wherein the risk score information includes a plurality of mapping relationships, and the mapping relationship is a mapping relationship between a cancer type and a risk score;

[0101] A variant gene-cancer type topology map is constructed based on each of the risk score information; the variant gene-cancer type topology map is the cancer risk gene screening result.

[0102] It should be noted that technicians in the relevant field can clearly understand that for the convenience and simplicity of description, the specific working process of the terminal device 200 described above can refer to the corresponding process of the aforementioned cancer risk gene screening method, and will not be repeated here.

[0103] An embodiment of the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by one or more processors, the one or more processors implement the cancer risk gene screening method provided in the embodiment of the present application.

[0104] The computer-readable storage medium may be an internal storage unit of the terminal device 200 in the aforementioned embodiment, such as a hard disk or memory of the terminal device 200. The computer-readable storage medium may also be an external storage device of the terminal device 200, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped with the terminal device 200.

[0105] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in the present application, and these modifications or replacements should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A method for screening cancer risk genes, characterized in that: Executed by a terminal device, the method includes: Acquire cfDNA sequencing data of the subject, and detect the cfDNA sequencing data based on a preset variant gene detection algorithm to obtain variant gene information of the subject; wherein the variant gene information includes at least one variant gene; For each of the variant genes, risk score information corresponding to the variant gene is generated based on a preset risk score algorithm; wherein the risk score information includes a plurality of mapping relationships, and the mapping relationship is a mapping relationship between a cancer type and a risk score; Constructing a variant gene-cancer type topology map based on each of the risk score information; the variant gene-cancer type topology map is a cancer risk gene screening result; The step of generating risk score information corresponding to the variant gene based on a preset risk score algorithm includes: Obtaining the correlation coefficients between the variant genes and each cancer type based on a preset Bayesian formula; Obtaining a global risk coefficient corresponding to the variant gene information based on a preset global risk coefficient calculation formula; For each of the cancer types, generating a risk score corresponding to the cancer type based on a preset risk score calculation formula, the global risk coefficient and a correlation coefficient corresponding to the cancer type, to obtain the risk score information; The Bayesian formula is shown in formula (1): （1） in, P(V cancer ) is the correlation coefficient; P ( V detected∣cancer ) is the conditional probability; P(cancer) is the basic probability; e −λf(ΔG) is an exponential decay term, which is used to reflect the effect of gene mutation on the change of protein free energy. λ is the regulating factor; f(Δ G) is the free energy change function; ΔG is the free energy change of protein before and after gene mutation; P(V detected) is the overall probability; N(V) is the background mutation rate; for each of the cancer types, when calculating the correlation coefficient between the cancer type and the variant gene, the conditional probability is the probability of detecting the variant gene in the patient corresponding to the cancer type, the basic probability is the probability of the cancer type appearing in the population, the overall probability is the probability of the variant gene appearing in the population, and the background mutation rate is the probability of the variant gene appearing in the non-cancer population.

2. The method for screening cancer risk genes according to claim 1, characterized in that: The global risk coefficient calculation formula is shown in formula (2): （2） in, I(V) is the global risk coefficient, B i For the i The centrality score corresponding to each variant gene in the gene regulatory network, W is the interaction strength between each variant gene, N i For the i The number of interactions corresponding to each variant gene in the gene regulatory network.

3. The method for screening cancer risk genes according to claim 1, characterized in that: The risk score calculation formula is shown in formula (3): （3） in, S(V) scoring the risk, I(V) is the global risk coefficient, P(V cancer ) is the correlation coefficient, N is the number of interactions corresponding to the variant gene in the gene regulatory network, B is the centrality score of the variant gene in the gene regulatory network.

4. The method for screening cancer risk genes according to claim 1, characterized in that: The step of constructing a variant gene-cancer type topology map based on each of the risk score information comprises: Arrange the variant genes corresponding to the risk score information in order from top to bottom to obtain a variant gene sequence; Deduplication processing is performed on all cancer types in each of the risk score information to obtain target cancer type information; the target cancer type information includes multiple target cancer types; Arrange the target cancer types in order from top to bottom to obtain a target cancer type sequence; Placing the target cancer type sequence to the right of the variant gene sequence; For each of the risk score information, the variant genes corresponding to the risk score information in the variant gene sequence and the target cancer types corresponding to each mapping relationship of the risk score information in the target cancer type sequence are respectively connected with straight lines, and the risk score corresponding to the target cancer type corresponding to the straight line in the risk score information is marked on each of the straight lines with a first font, to obtain an initial variant gene-cancer type topology map; For each variant gene on the initial variant gene-cancer type topology map, the risk scores corresponding to each straight line corresponding to the variant gene on the initial variant gene-cancer type topology map are added to obtain a gene risk score corresponding to the variant gene, and the gene risk score is marked next to the variant gene in a second font to obtain an intermediate variant gene-cancer type topology map; For each cancer type on the intermediate variant gene-cancer type topology map, the risk scores corresponding to each straight line corresponding to the cancer type on the initial variant gene-cancer type topology map are added to obtain the cancer risk score corresponding to the cancer type, and the cancer risk score is marked next to the cancer type in a third font to obtain the variant gene-cancer type topology map.

5. The method for screening cancer risk genes according to claim 1, characterized in that: The method further comprises: Obtaining a test code of the test subject; the test code includes a plurality of numbers and a plurality of letters; Encoding the mutant gene-cancer type topological map based on a preset encoding rule to obtain a coding sequence; The coding sequence is segmented based on the number of letters to obtain a plurality of coding units, and the coding units are arranged in sequence based on the corresponding order of the coding units in the coding sequence to obtain a coding unit sequence; wherein the number of the coding units is consistent with the number of letters; Performing hash operations on each of the letters based on a preset hash algorithm to obtain a hash value corresponding to each letter, and arranging each of the hash values ​​in sequence based on the order of the letters corresponding to each of the hash values ​​in the checked code to obtain a hash value sequence; For each coding unit in the coding unit sequence, a target hash value corresponding to the coding unit is determined in the hash value sequence, and the coding unit is encrypted based on the target hash value to obtain an encrypted coding unit corresponding to the coding unit, and the encrypted coding unit is packaged based on a preset package processing method to obtain a target data packet corresponding to the encrypted coding unit; wherein the order of the coding units in the coding unit sequence is consistent with the order of the target hash values ​​in the hash value sequence; For each of the numbers, a data packet unit corresponding to the number is generated based on a preset data packet unit generation method, and the number of data packets in the data packet unit is consistent with the number; Arrange the data packet units in sequence based on the order of the numbers corresponding to the data packet units in the checked code to obtain a data packet unit sequence; For each of the letters, based on the order of the letters in the checked code and the order of the numbers corresponding to each of the data packet units in the checked code, determine the interpolation position corresponding to the letter in the data packet unit sequence; For each of the target data packets, insert the target data packet into the interpolation position corresponding to the letter corresponding to the target data packet to obtain a target data packet sequence; Each data packet of the target data packet sequence is sent to the subject in sequence.

6. A cancer risk gene screening device, characterized in that: include: An acquisition module, used to acquire cfDNA sequencing data of the subject, and detect the cfDNA sequencing data based on a preset variant gene detection algorithm to obtain variant gene information of the subject; wherein the variant gene information includes at least one variant gene; A scoring module, for generating risk score information corresponding to each of the variant genes based on a preset risk scoring algorithm; wherein the risk score information includes a plurality of mapping relationships, and the mapping relationship is a mapping relationship between a cancer type and a risk score; A construction module is used to construct a variant gene-cancer type topology map based on each of the risk score information; the variant gene-cancer type topology map is a cancer risk gene screening result; The step of generating risk score information corresponding to the variant gene based on a preset risk score algorithm includes: Obtaining the correlation coefficients between the variant genes and each cancer type based on a preset Bayesian formula; Obtaining a global risk coefficient corresponding to the variant gene information based on a preset global risk coefficient calculation formula; For each of the cancer types, generating a risk score corresponding to the cancer type based on a preset risk score calculation formula, the global risk coefficient and a correlation coefficient corresponding to the cancer type, to obtain the risk score information; The Bayesian formula is shown in formula (1): （1） in, P(V cancer ) is the correlation coefficient; P ( V detected∣cancer ) is the conditional probability; P(cancer) is the basic probability; e −λf(ΔG) is an exponential decay term, which is used to reflect the effect of gene mutation on the change of protein free energy. λ is the regulating factor; f(Δ G) is the free energy change function; ΔG is the free energy change of protein before and after gene mutation; P(V detected) is the overall probability; N(V) is the background mutation rate; for each of the cancer types, when calculating the correlation coefficient between the cancer type and the variant gene, the conditional probability is the probability of detecting the variant gene in the patient corresponding to the cancer type, the basic probability is the probability of the cancer type appearing in the population, the overall probability is the probability of the variant gene appearing in the population, and the background mutation rate is the probability of the variant gene appearing in the non-cancer population.

7. A terminal device, characterized in that: The terminal device includes a processor, a memory, and a computer program stored in the memory and executable by the processor, wherein when the computer program is executed by the processor, the method for screening cancer risk genes as described in any one of claims 1 to 5 is implemented.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, wherein when the computer program is executed by a processor, the method for screening cancer risk genes according to any one of claims 1 to 5 is implemented.

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